Various machine translation technologies for translation of one language to another are known, as well as techniques and technologies for improving the accuracy of machine translation of languages.
There is also significant demand for machine translation embodied in an interface to computer systems and computer programs. This includes use of machine translation as a means of activating cross language functions on a computer system or computer program, especially for example when a user is travelling to other countries.
There are generally two categories of machine translation methods and systems. The first category includes statistics based machine translation methods and systems which generally require a large bilingual training set to improve the accuracy of the machine translation output. The output of such method and system usually has better word coverage, but the grammar is typically poor, which makes it very hard to be understood. The second category includes grammar based machine translation methods and systems. The accuracy of this system is ensured by grammar patterns which are often prepared manually for a given subject area. Therefore, the vocabulary coverage is usually very limited, and it is difficult to extend such methods and systems to other languages or other subject areas.
These disadvantages are a practical obstacle to the design and implementation of machine translation technologies that are accurate enough for widespread user adoption. For example, the development of cross language Question Answering (QA) systems to enable cross language question answering are not practical based on prior art solutions because such an application requires the grammar of translation results to be correct and the scope of the domain to be relatively unlimited.
Thus, there is a need for a computer system, computer program, and computer implemented method that addresses at least some of the above mentioned obstacles. There is a further need for a QA system that provides improved language translation accuracy and therefore enables cross language QA services that address a significant segment of the population of interest, including individuals for whom English is not their first language.